Online Master's in Data Science for Jobs in Michigan

Signaling Michigan’s full commitment to expanding resources for data scientists and attracting strong talent in this field, University of Michigan hosted a 2015 symposium on data science featuring top professionals from across the nation. The symposium culminated in an announcement by the university that it was investing $100 million to create a new data science undergraduate major.

The growing importance and demand for data scientists in Michigan is underscored by some basic facts. Michigan’s largest employers are listed by sector with total employment figures from the US Department of Commerce (all figures for 2014):

  • State of Michigan, employing 44,853 – total state and local government employment: 536,943
  • Spectrum Health Systems, employing 17,324 – total healthcare industry employment: 554,466
  • General Motors, employing 14,443 – total motor vehicle manufacturing employment: 170,984

A 2011 report published by international management consulting firm McKinsey & Company singles out these three economic sectors to demonstrate the important role data science has been playing in enterprises in Michigan and around the world. Given how these are the main economic sectors in the state, the demand and necessity for data scientists should continue to skyrocket. The McKinsey report details the following:

  • Government sector – data scientists could save the government sector more than $100 billion by making operational efficiency improvements
  • Healthcare sector – data scientists can potentially generate $300 billion in value for this sector by reducing expenditures, improving efficiency, and bettering the quality of care
  • Manufacturing sector – data scientists can boost retail sales of manufactured products by over 60 percent by embedding sensors in products that communicate after-service data directly to the manufacturer, such as the need for preventative maintenance

Becoming a data scientist in Michigan and moving towards a successful career starts with the right education, work experience, and skills.

Preparing to Enroll in a Master’s Degree Program in Data Science

Preparation for a master’s degree in data science starts with an appropriate undergraduate degree, developing key proficiencies and gaining relevant work experience.

While each data science master’s program may have its own admission criteria, many require at least five years of pertinent work experience as a minimum condition for admittance. Applicants may also need to prove their competency through high scores on GRE and/or GMAT exams and fill gaps in functional knowledge through massive open online courses (MOOCs) and bridge programs.

Undergraduate Degree and Master’s Prerequisite Courses

Academically speaking, students should approach a master’s in data science with an undergraduate degree in a quantitative field, such as applied math, computer science, statistics, or engineering. A cumulative GPA should not be below 3.0. A prospective student’s undergraduate course load should be rich in key disciplines such as:

  • Statistics
  • Calculus I and II
  • programming languages
  • Quantitative methods
  • Linear algebra

Relevant Personal and Work Experience for Admissions

Competitive data science graduate programs have the luxury of choosing students from highly compatible backgrounds. This means students who:

  • Have at least five years of work experience that demonstrates technical and quantitative skills
  • Have personal experience that relates to hacking, coding, mathematics, database administration, statistics, data mining, or programming

Having a good employment record is also critical for securing the letters of recommendation that are necessary for graduate school admissions applications. Some examples of potentially qualifying work experience in Michigan may include:

  • Providing IT services like database management for the University of Michigan
  • Working with General Motors to provide any analytical services that relate to a range of fields from human resources or supply to productivity and sales
  • Working within the healthcare industry, such as with Spectrum Health Systems, to establish, maintain, or analyze statistics
  • Provide computer programming or cyber security services for the State of Michigan

Succeeding on GRE/GMAT Exams

Graduate schools expect that applicants should score in at least the 85th percentile of a GRE or GMAT exam. The companies that sponsor these exams and others provide students with resources for preparation.

GRE The Graduate Record Exam (GRE) revised general test’s quantitative reasoning section evaluates the following:

  • Arithmetic topics including integers, factorization, exponents, and roots
  • Data analysis, covering topics like statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
  • Algebraic topics such as algebraic expressions, functions, linear equations, quadratic equations, and graphing
  • Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem

Students can prepare for the quantitative reasoning section by reviewing Educational Testing Service’s (ETS) Math Review. GRE practice exams are available through the Princeton Review and Veritas Prep.

The GRE is also offered in two relevant subject tests, covering the following topics:

Physics – physics test practice book

  • Classical mechanics
  • Electromagnetism
  • Optics and waves
  • Thermodynamics
  • Statistical mechanics
  • Quantum mechanics
  • Atomic physics
  • Special relativity
  • Lab methods and specialized topics

Mathematics – mathematics test practice book

  • Calculus
  • Algebra
  • Introductory real analysis
  • Discrete mathematics
  • Probability, statistics, and numerical analysis

GMAT – The Graduate Management Admissions Test’s (GMAT) quantitative section evaluates a student’s skills as they relate to data analysis. One of the four sections of the GMAT, the quantitative section is comprised of 37 questions to be completed in 75 minutes. All of the questions pertain to data sufficiency and problem solving.

GMAT practice exams are available through the Princeton Review and Veritas Prep.

MOOCs and Bridge Courses: Filling Gaps in Functional Knowledge 

MOOCs – Massive open online courses take the form of recorded lectures, discussions, and interactive user forums that involve students, professors, and teaching assistants. These can be a valuable resource when it comes to filling in missing pieces in a prospective graduate student’s academic or personal history. MOOCs can range from open-access courses to those reserved specifically for aspiring data scientists.

Bridge Courses – Because data science incorporates skills from several fields – engineering, programming, communications, statistics, and product knowledge to name a few – students may need to complete an academic regimen prior to transitioning to graduate-level coursework. Schools that house data science master’s programs make pre-master’s bridge courses available to students that have already been accepted into the program. Bridge courses typically take 15 weeks to complete, after which students would begin their master’s-level coursework.

Fundamental bridge programs:

  • Algorithms
  • Analysis of algorithms
  • Linear algebra
  • Data structures

Bridge programs for code programming:

  • JAVA
  • C++
  • Python
  • Rstudio

Earning a Master’s Degree in Data Science in Michigan

As a newly established field, undergraduate programs in data science have sprung up in cities like Ann Arbor and Kalamazoo. Michigan also has one school offering a Master of Science in Data Science in Houghton, and one school offering a graduate certificate in data science in Ann Arbor.

Students also have the option of completing their graduate degree online. Examples of online data science graduate programs available to students in Michigan include:

  • Master of Science (MS) in Data Science
  • Master of Information and Data Science (MIDS)
  • Master of Science in Data Science (MSDS)
  • Online Graduate Certificate in Data Science
  • Data Mining and Applications Graduate Certificate

A full master’s degree program includes approximately 30 semester credits. Completion times for a graduate program in data science vary, depending on the options offered by the school:

  • Traditional completion time – approximately 18 months or three semesters
  • Accelerated completion – completion in as little as 12 months or two semesters
  • Part-time – completion in as much as 32 months or five semesters
  • Graduate certificate programs can be completed in one or two semesters

Core Curriculum and Immersion

Master’s students learn about core curriculum subjects that include:

  • Machine learning and artificial intelligence
  • Statistical sampling
  • Information visualization
  • Ethics and law for data science
  • Data mining
  • Network and data security
  • Experiments and casual inference
  • Quantifying materials
  • Scaling macro and micro data
  • File organization and database management
  • Data storage and retrieval
  • Advanced managerial economics
  • Applied regression and time series analysis
  • Experimental statistics
  • Data research design and applications
  • Visualization of data
  • Immersion

Students complete an immersion process towards the end of their program, which represents a real-world application of skills developed up to that point. The immersion process involves work on a capstone project and allows students to demonstrate their competencies to their professors as well as visiting potential employers.

Key Competencies and Objectives

Students who earn a master’s degree in data science would have achieved mastery of these core competencies:

  • Familiarity with hash algorithms, cyphers, and secure communications protocols
  • At least moderate fluency in programming languages such as GitHub, SAS, Python, and Shiny
  • Ability to conduct association mining and cluster analysis
  • Ability to run an analysis of survey data
  • Ability to develop innovative design and research methods
  • Ability to work in teams to achieve specific goals
  • Ability to interpret and communicate results
  • Ability to develop and conduct sophisticated data analyses
  • Ability to conduct database queries

Career Opportunities in Michigan for Data Scientists with Advanced Degrees

Major employers like the State of Michigan, auto manufacturers, and healthcare companies like Spectrum are aggressively recruiting qualified data scientists from throughout the nation to work in Michigan. As the state’s major employers, these exemplify the demand for data scientists that is growing across all of the state’s economic sectors, a fact that holds true even down to some of Michigan’s smallest employers. For example, the venture-backed Detroit startup Project X LLC was recruiting for a data scientist at the same time as Ford Motor Company.

Readers will notice how new the field of data science is as companies list requirements that specify a master’s degree in, “a quantitative field.” Many of today’s candidates with graduate degrees did not have the option of obtaining a master’s degree in data science since graduate programs specific to the field were not yet developed.

(The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment. These examples were taken from a survey of job vacancy announcements for data scientists in Michigan, completed in February 2016):

Data Scientist with Ford Motor Company in Dearborn

  • Work with Ford’s global data, insight, and analytics department
  • Data scientist is responsible for all phases of data creation, model development, and model deployment with the goal of creating dealer profiles
  • Applicants must have a master’s degree in a qualitative field like statistics, economics, quantitative finance, industrial systems and engineering, or mathematics

Data Scientist Analyst with Altair ProductDesign in Dearborn

  • A global product development consultancy and subsidiary of Altair Engineering
  • Responsibilities include ensuring that data is accurate, and that policies regarding quality, risk management, business management, and data management are followed
  • Preferred applicants hold a master’s degree and have two years of experience in a big data environment

Data Scientist with Spectrum Health in Grand Rapids

  • Work as part of Spectrum Health’s consumer and market intelligence team
  • Duties involve using data to solve core business problems, as well as building and designing analytical systems to provide insight for business strategy development
  • Applicants must have at least a master’s degree in a quantitative field, such as STEM, statistics, bioinformatics, epidemiology, or computer science

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